Emotions Studied by Imaging of the Human Brain:The Somatic and Emotional Motor Systems

The brain has only two goals, survival of the individual and survival of the species. One of the most important tools to accomplish these goals is the motor system, which includes the somatic or voluntary motor system and the emotional motor system (EMS). The EMS is equally or even more important than the somatic motor system. In humans, the cortex cerebri with the corticospinal tract plays the most important role in the somatic motor system, while in the EMS, the periaqueductal gray (PAG) plays a central role controlling nociception, cardiovascular changes, respiration, micturition, parturition, defecation, vocalization, vomiting, coughing, sneezing, mating behavior, pupil dilation, and defensive posture.</p

Modeling Power Systems Dynamics with Symbolic Physics-Informed Neural Networks

In recent years, scientific machine learning, particularly physic-informed neural networks (PINNs), has introduced new innovative methods to understanding the differential equations that describe power system dynamics, providing a more efficient alternative to traditional methods. However, using a single neural network to capture patterns of all variables requires a large enough size of networks, leading to a long time of training and still high computational costs. In this paper, we utilize the interfacing of PINNs with symbolic techniques to construct multiple single-output neural networks by taking the loss function apart and integrating it over the relevant domain. Also, we reweigh the factors of the components in the loss function to improve the performance of the network for instability systems. Our results show that the symbolic PINNs provide higher accuracy with significantly fewer parameters and faster training time. By using the adaptive weight method, the symbolic PINNs can avoid the vanishing gradient problem and numerical instability